What happened
It was reported that on 29 January 2024 a 9News Melbourne bulletin, covering the Victorian government’s position on duck hunting, used a still image of Georgie Purcell, a member of the Victorian Legislative Council for the Animal Justice Party and a prominent campaigner against the practice. In the broadcast image, the dress Purcell had worn in the original photograph appeared as separates that exposed her midriff, and her chest appeared enlarged. Purcell posted the two images side by side, said the network had edited her body and her outfit, and described the result as sexist, adding that she could not imagine it happening to a male colleague. She later spoke on ABC RN Breakfast about AI-augmented imagery and the way it falls on women.
Nine apologised. The director of news in Melbourne, Hugh Nailon, said the graphics department had sourced an image of Purcell online and resized it to fit the bulletin’s specifications, and that during that process automation in Adobe Photoshop had produced a picture that was not consistent with the original, which did not meet the network’s editorial standards. The tool at issue was Photoshop’s generative fill, and its generative expand option, which extends a picture beyond its original frame by inventing plausible content to fill the new space, powered by Adobe’s Firefly model. Adobe, whose software had been named as the cause, responded that any changes of this kind to the image would have required human intervention and approval, that its generative features do not run and publish alterations on their own. The two accounts did not reconcile: Nine described an automated step that overreached, and the tool’s maker described a process a person has to direct and accept. What was never produced publicly was the record that would have settled it: the source image, the edits applied to it, and the person who approved it before it went to air.
What an auditable version would have shown
The dispute between Nine and Adobe came down to a missing record. A newsroom that alters a photograph holds, or should hold, the evidence of what it did: the original file, each tool applied to it, the parameters of any generative step, and the sign-off of the editor who released it. With that record, the claim that automation alone changed the image is either shown to be true or shown not to be, in seconds, from the file’s own history rather than from competing statements days later. This is not hypothetical tooling. Adobe’s own Content Authenticity Initiative, begun in 2019, attaches content credentials to an image, a tamper-evident log of what device made it and what edits were performed, precisely so that an altered picture arrives carrying its own provenance. That system already existed, and whatever was used to make this image, the picture that went to air did not carry those credentials.
Where the gap was
An image of a real person was altered and published, and no record was produced to show what had been changed or by whom. A ConstraintGate encodes the standing editorial rule as a check that runs before publication: a generative alteration of a real person’s photograph is not released without disclosure and a named human approval, so the rule is enforced at the moment of use rather than recalled in an apology. A ConductRecord preserves the picture’s history, the source file, the tools and generative parameters applied, and the editor who signed it off, as a signed and reviewable entry, so that responsibility for what a tool and a person did together can be read from the file instead of contested between the outlet and the software vendor.
What governance should have looked like
When a tool and a person both handle an image, “the automation did it” can only be assessed against a record, and here there was none to check. Two decisions sit behind the published picture: running the generative tool, and releasing what it produced. Best practice would be for a media organisation that publishes an altered image of a real person to be able to show, from its own history, what was done to the image and who approved its release, so that responsibility rests with a named person rather than an unresolved dispute with the software vendor.
Failure Pattern: a generative tool altered a real person’s published image, and no provenance record could show what was changed, by what, or who approved it.
Governance Principle: a published image of a real person should carry a verifiable record of its source and every edit applied, so an alteration is disclosed rather than deniable.
The reference implementation of ConstraintGate and ConductRecord is open source. It lives at github.com/saffronandindia/headlights-oss, Apache 2.0 licensed and free to install. The repository is public now.
Sources
- Adobe confirms edited image of Georgie Purcell would have required ‘human intervention’ (Women’s Agenda)
- Nine challenged on ‘automation’ excuse for Georgie Purcell image (Crikey)
- Nine was slammed for ‘AI editing’ a Victorian MP’s dress. How can news media use AI responsibly? (The Conversation)
- Nine Network cites Photoshop AI error for edited Georgie Purcell image (The Washington Post)